Network imaging biomarkers: insights and clinical applications in Parkinson's disease

• Published in: Lancet neurology Vol. 17; no. 7; pp. 629 - 640
• Main Authors: Schindlbeck, Katharina A, Eidelberg, David
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01-07-2018; Elsevier Limited
• Subjects: Algorithms; Alzheimer's disease; Animal models; Basal ganglia; Biomarkers; Brain; Central nervous system diseases; Clinical trials; Differential diagnosis; Disease Progression; Humans; Medical imaging; Metabolism; Movement disorders; Nerve Net - abnormalities; Nerve Net - diagnostic imaging; Neurodegenerative diseases; Neuroimaging; Parkinson Disease - diagnostic imaging; Parkinson Disease - metabolism; Parkinson's disease; Patients; REM sleep; Scanners; Sleep disorders; Surgery; Therapeutic applications
• ISSN: 1474-4422; 1474-4465
• DOI: 10.1016/S1474-4422(18)30169-8

Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders.